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Automated Quantitative Analysis of p53, Cyclin D1, Ki67 and pERK Expression in Breast Carcinoma Does Not Differ from Expert Pathologist Scoring and Correlates with Clinico-Pathological Characteristics.
- Source :
-
Cancers . Sep2012, Vol. 4 Issue 3, p725-742. 18p. 1 Color Photograph, 3 Charts, 3 Graphs. - Publication Year :
- 2012
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Abstract
- There is critical need for improved biomarker assessment platforms which integrate traditional pathological parameters (TNM stage, grade and ER/PR/HER2 status) with molecular profiling, to better define prognostic subgroups or systemic treatment response. One roadblock is the lack of semi-quantitative methods which reliably measure biomarker expression. Our study assesses reliability of automated immunohistochemistry (IHC) scoring compared to manual scoring of five selected biomarkers in a tissue microarray (TMA) of 63 human breast cancer cases, and correlates these markers with clinico-pathological data. TMA slides were scanned into an Ariol Imaging System, and histologic (H) scores (% positive tumor area x staining intensity 0-3) were calculated using trained algorithms. H scores for all five biomarkers concurred with pathologists' scores, based on Pearson correlation coefficients (0.80-0.90) for continuous data and Kappa statistics (0.55-0.92) for positive vs. negative stain. Using continuous data, significant association of pERK expression with absence of LVI (p = 0.005) and lymph node negativity (p = 0.002) was observed. p53 over-expression, characteristic of dysfunctional p53 in cancer, and Ki67 were associated with high grade (p = 0.032 and 0.0007, respectively). Cyclin D1 correlated inversely with ER/PR/HER2-ve (triple negative) tumors (p = 0.0002). Thus automated quantitation of immunostaining concurs with pathologists' scoring, and provides meaningful associations with clinico-pathological data. [ABSTRACT FROM AUTHOR]
- Subjects :
- *BIOMARKERS
*BIOCHEMISTRY
*TUMORS
*PATHOLOGY
*IMMUNOHISTOCHEMISTRY
*HISTOPATHOLOGY
*THERAPEUTIC use of biochemical markers
*BREAST cancer prognosis
*ACADEMIC medical centers
*CONFIDENCE intervals
*STATISTICAL correlation
*EPIDEMIOLOGY
*FISHER exact test
*RESEARCH funding
*STATISTICS
*SURVIVAL
*TUMOR classification
*DATA analysis
*RECEIVER operating characteristic curves
*DATA analysis software
*MICROARRAY technology
Subjects
Details
- Language :
- English
- ISSN :
- 20726694
- Volume :
- 4
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Cancers
- Publication Type :
- Academic Journal
- Accession number :
- 80917716
- Full Text :
- https://doi.org/10.3390/cancers4030725